Biblio

Failing to properly isolate components in the same address space has resulted in a substantial amount of vulnerabilities. Enforcing the least privilege principle for memory accesses can selectively isolate software components to restrict attack surface and prevent unintended cross-component memory corruption. However, the boundaries and interactions between software components are hard to reason about and existing approaches have failed to stop attackers from exploiting vulnerabilities caused by poor isolation. We present the secure memory views (SMV) model: a practical and efficient model for secure and selective memory isolation in monolithic multithreaded applications. SMV is a third generation privilege separation technique that offers explicit access control of memory and allows concurrent threads within the same process to partially share or fully isolate their memory space in a controlled and parallel manner following application requirements. An evaluation of our prototype in the Linux kernel (TCB textless 1,800 LOC) shows negligible runtime performance overhead in real-world applications including Cherokee web server (textless 0.69%), Apache httpd web server (textless 0.93%), and Mozilla Firefox web browser (textless 1.89%) with at most 12 LOC changes.

We consider the following natural generalization of Binary Search: in a given undirected, positively weighted graph, one vertex is a target. The algorithm’s task is to identify the target by adaptively querying vertices. In response to querying a node q, the algorithm learns either that q is the target, or is given an edge out of q that lies on a shortest path from q to the target. We study this problem in a general noisy model in which each query independently receives a correct answer with probability p textgreater 1/2 (a known constant), and an (adversarial) incorrect one with probability 1 − p. Our main positive result is that when p = 1 (i.e., all answers are correct), log2 n queries are always sufficient. For general p, we give an (almost information-theoretically optimal) algorithm that uses, in expectation, no more than (1 − δ) logn/1 − H(p) + o(logn) + O(log2 (1/δ)) queries, and identifies the target correctly with probability at leas 1 − δ. Here, H(p) = −(p logp + (1 − p) log(1 − p)) denotes the entropy. The first bound is achieved by the algorithm that iteratively queries a 1-median of the nodes not ruled out yet; the second bound by careful repeated invocations of a multiplicative weights algorithm. Even for p = 1, we show several hardness results for the problem of determining whether a target can be found using K queries. Our upper bound of log2 n implies a quasipolynomial-time algorithm for undirected connected graphs; we show that this is best-possible under the Strong Exponential Time Hypothesis (SETH). Furthermore, for directed graphs, or for undirected graphs with non-uniform node querying costs, the problem is PSPACE-complete. For a semi-adaptive version, in which one may query r nodes each in k rounds, we show membership in Σ2k−1 in the polynomial hierarchy, and hardness for Σ2k−5.

Modern static bug finding tools are complex. They typically consist of hundreds of thousands of lines of code, and most of them are wedded to one language (or even one compiler). This complexity makes the systems hard to understand, hard to debug, and hard to retarget to new languages, thereby dramatically limiting their scope. This paper reduces checking system complexity by addressing a fundamental assumption, the assumption that checkers must depend on a full-blown language specification and compiler front end. Instead, our program checkers are based on drastically incomplete language grammars ("micro-grammars") that describe only portions of a language relevant to a checker. As a result, our implementation is tiny-roughly 2500 lines of code, about two orders of magnitude smaller than a typical system. We hope that this dramatic increase in simplicity will allow people to use more checkers on more systems in more languages. We implement our approach in μchex, a language-agnostic framework for writing static bug checkers. We use it to build micro-grammar based checkers for six languages (C, the C preprocessor, C++, Java, JavaScript, and Dart) and find over 700 errors in real-world projects.

Recommender systems have become quite popular recently. However, such systems are vulnerable to several types of attacks that target user ratings. One such attack is the Sybil attack where an entity masquerades as several identities with the intention of diverting user ratings. In this work, we propose evolutionary game theory as a possible solution to the Sybil attack in recommender systems. After modeling the attack, we use replicator dynamics to solve for evolutionary stable strategies. Our results show that under certain conditions that are easily achievable by a system administrator, the probability of an attack strategy drops to zero implying degraded fitness for Sybil nodes that eventually die out.

Many modern cyber-physical systems (CPS), especially industrial automation systems, require the actions of multiple computational systems to be performed at much higher rates and more tightly synchronized than is possible with ad hoc designs. Time is the common entity that computing and physical systems in CPS share, and correct interfacing of that is essential to flawless functionality of a CPS. Fundamental research is needed on ways to synchronize clocks of computing systems to a high degree, and on design methods that enable building blocks of CPS to perform actions at specified times. To realize the potential of CPS in the coming decades, suitable ways to specify distributed CPS applications are needed, including their timing requirements, ways to specify the timing of the CPS components (e.g. sensors, actuators, computing platform), timing analysis to determine if the application design is possible using the components, confident top-down design methodologies that can ensure that the system meets its timing requirements, and ways and methodologies to test and verify that the system meets the timing requirements. Furthermore, strategies for securing timing need to be carefully considered at every CPS design stage and not simply added on. This paper exposes these challenges of CPS development, points out limitations of previous approaches, and provides some research directions towards solving these challenges.

With the advent of the Internet of Things (IoT), billions of devices are expected to continuously collect and process sensitive data (e.g., location, personal health). Due to limited computational capacity available on IoT devices, the current de facto model for building IoT applications is to send the gathered data to the cloud for computation. While private cloud infrastructures for handling large amounts of data streams are expensive to build, using low cost public (untrusted) cloud infrastructures for processing continuous queries including on sensitive data leads to concerns over data confidentiality. This paper presents STYX, a novel programming abstraction and managed runtime system, that ensures confidentiality of IoT applications whilst leveraging the public cloud for continuous query processing. The key idea is to intelligently utilize partially homomorphic encryption to perform as many computationally intensive operations as possible in the untrusted cloud. STYX provides a simple abstraction to the IoT developer to hide the complexities of (1) applying complex cryptographic primitives, (2) reasoning about performance of such primitives, (3) deciding which computations can be executed in an untrusted tier, and (4) optimizing cloud resource usage. An empirical evaluation with benchmarks and case studies shows the feasibility of our approach.

In-depth consideration and evaluation of security and resilience is necessary for developing the scientific foundations and technology of Cyber-Physical Systems (CPS). In this demonstration, we present SURE [1], a CPS experimentation and evaluation testbed for security and resilience focusing on transportation networks. The testbed includes (1) a heterogeneous modeling and simulation integration platform, (2) a Web-based tool for modeling CPS in adversarial environments, and (3) a framework for evaluating resilience using attacker-defender games. Users such as CPS designers and operators can interact with the testbed to evaluate monitoring and control schemes that include sensor placement and traffic signal configuration.

Security isolation is a foundation of computing systems that enables resilience to different forms of attacks. This article seeks to understand existing security isolation techniques by systematically classifying different approaches and analyzing their properties. We provide a hierarchical classification structure for grouping different security isolation techniques. At the top level, we consider two principal aspects: mechanism and policy. Each aspect is broken down into salient dimensions that describe key properties. We break the mechanism into two dimensions, enforcement location and isolation granularity, and break the policy aspect down into three dimensions: policy generation, policy configurability, and policy lifetime. We apply our classification to a set of representative articles that cover a breadth of security isolation techniques and discuss tradeoffs among different design choices and limitations of existing approaches.

The Security Behavior Intentions Scale (SeBIS) measures the computer security attitudes of end-users. Because intentions are a prerequisite for planned behavior, the scale could therefore be useful for predicting users' computer security behaviors. We performed three experiments to identify correlations between each of SeBIS's four sub-scales and relevant computer security behaviors. We found that testing high on the awareness sub-scale correlated with correctly identifying a phishing website; testing high on the passwords sub-scale correlated with creating passwords that could not be quickly cracked; testing high on the updating sub-scale correlated with applying software updates; and testing high on the securement sub-scale correlated with smartphone lock screen usage (e.g., PINs). Our results indicate that SeBIS predicts certain computer security behaviors and that it is a reliable and valid tool that should be used in future research.

Phishing is one of the most dangerous information security threats present in the world today, with losses toping 5.9 billion dollars in 2013. Evolving from the original concept of phishing, spear phishing also attempts to scam individuals online, however it uses personalized mail to yield a far higher success rate. This paper suggests an increased threat of spear phishing success due to the presence of social media. Assessing this new threat is important not only to the individuals, but also to companies whose employees may specifically be targeted through their social media accounts. The paper presents the design and implementation of an architecture to determine phishing susceptibility of a user through their social media accounts, and methods to reduce the threat. Preliminary testing shows that social media provides a publicly accessible resource to assess targeted individuals for phishing attacks through their accounts.

The usual approach to security for cloud-hosted applications is strong separation. However, it is often the case that the same data is used by different applications, particularly given the increase in data-driven (`big data' and IoT) applications. We argue that access control for the cloud should no longer be application-specific but should be data-centric, associated with the data that can flow between applications. Indeed, the data may originate outside cloud services from diverse sources such as medical monitoring, environmental sensing etc. Information Flow Control (IFC) potentially offers data-centric, system-wide data access control. It has been shown that IFC can be provided at operating system level as part of a PaaS offering, with an acceptable overhead. In this paper we consider how IFC can be integrated with application-specific access control, transparently from application developers, while building from simple IFC primitives, access control policies that align with the data management obligations of cloud providers and tenants.

This paper proposes a taxonomy of autonomous vehicle handover situations with a particular emphasis on situational awareness. It focuses on a number of research challenges such as: legal responsibility, the situational awareness level of the driver and the vehicle, the knowledge the vehicle must have of the driver's driving skills as well as the in-vehicle context. The taxonomy acts as a starting point for researchers and practitioners to frame the discussion on this complex problem.

In international military coalitions, situation awareness is achieved by gathering critical intel from different authorities. Authorities want to retain control over their data, as they are sensitive by nature, and, thus, usually employ their own authorization solutions to regulate access to them. In this paper, we highlight that harmonizing authorization solutions at the coalition level raises many challenges. We demonstrate how we address authorization challenges in the context of a scenario defined by military experts using a prototype implementation of SAFAX, an XACML-based architectural framework tailored to the development of authorization services for distributed systems.

We propose a new security paradigm that makes cross-layer personalization a premier component in the design of security solutions for computer infrastructure and situational awareness. This paradigm is based on the observation that computer systems have a personalized usage profile that depends on the user and his activities. Further, it spans the various layers of abstraction that make up a computer system, as if the user embedded his own DNA into the computer system. To realize such a paradigm, we discuss the design of a comprehensive and cross-layer profiling approach, which can be adopted to boost the effectiveness of various security solutions, e.g., malware detection, insider attacker prevention and continuous authentication. The current state-of-the-art in computer infrastructure defense solutions focuses on one layer of operation with deployments coming in a "one size fits all" format, without taking into account the unique way people use their computers. The key novelty of our proposal is the cross-layer personalization, where we derive the distinguishable behaviors from the intelligence of three layers of abstraction. First, we combine intelligence from: a) the user layer, (e.g., mouse click patterns); b) the operating system layer; c) the network layer. Second, we develop cross-layer personalized profiles for system usage. We will limit our scope to companies and organizations, where computers are used in a more routine and one-on-one style, before we expand our research to personally owned computers. Our preliminary results show that just the time accesses in user web logs are already sufficient to distinguish users from each other,with users of the same demographics showing similarities in their profiles. Our goal is to challenge today's paradigm for anomaly detection that seems to follow a monoculture and treat each layer in isolation. We also discuss deployment, performance overhead, and privacy issues raised by our paradigm.

Detection of previously unknown attacks and malicious messages is a challenging problem faced by modern network intrusion detection systems. Anomaly-based solutions, despite being able to detect unknown attacks, have not been used often in practice due to their high false positive rate, and because they provide little actionable information to the security officer in case of an alert. In this paper we focus on intrusion detection in industrial control systems networks and we propose an innovative, practical and semantics-aware framework for anomaly detection. The network communication model and alerts generated by our framework are userunderstandable, making them much easier to manage. At the same time the framework exhibits an excellent tradeoff between detection rate and false positive rate, which we show by comparing it with two existing payload-based anomaly detection methods on several ICS datasets.

With cyber-physical systems opening to the outside world, security can no longer be considered a secondary issue. One of the key aspects in security of cyber-phyiscal systems is to deal with intrusions. In this paper, we highlight the several unique properties of control applications in cyber-physical systems. Using these unique properties, we propose a systematic intrusion-damage assessment and mitigation mechanism for the class of observable and controllable attacks. On the one hand, in cyber-physical systems, the plants follow certain laws of physics and this can be utilized to address the intrusion-damage assessment problem. That is, the states of the controlled plant should follow those expected according to the physics of the system and any major discrepancy is potentially an indication of intrusion. Here, we use a machine learning algorithm to capture the normal behavior of the system according to its dynamics. On the other hand, the control performance strongly depends on the amount of allocated resources and this can be used to address the intrusion-damage mitigation problem. That is, the intrusion-damage mitigation is based on the idea of allocating more resources to the control application under attack. This is done using a feedback-based approach including a convex optimization.

Today, cloud vendors host third party black-box services, whose developers usually provide only textual descriptions or purely syntactical interface specifications. Cloud vendors that give substantial support to other third party developers to integrate hosted services into new software solutions would have a unique selling feature over their competitors. However, to reliably determine if a service is reusable, comprehensive service specifications are needed. Characteristic for comprehensive in contrast to syntactical specifications are the formalization of ontological and behavioral semantics, homogeneity according to a global ontology, and a service grounding that links the abstract service description and its technical realization. Homogeneous, semantical specifications enable to reliably identify reusable services, whereas the service grounding is needed for the technical service integration. In general, comprehensive specifications are not available and have to be derived. Existing automatized approaches are restricted to certain characteristics of comprehensiveness. In my PhD, I consider an automatized approach to derive fully-fledged comprehensive specifications for black-box services. Ontological semantics are derived from syntactical interface specifications. Behavioral semantics are mined from call logs that cloud vendors create to monitor the hosted services. The specifications are harmonized over a global ontology. The service grounding is established using traceability information. The approach enables third party developers to compose services into complex systems and creates new sales channels for cloud and service providers.

Processes to automate the selection of appropriate algorithms for various matrix computations are described. In particular, processes to check for, and certify, various matrix properties of black-box matrices are presented. These include sparsity patterns and structural properties that allow "superfast" algorithms to be used in place of black-box algorithms. Matrix properties that hold generically, and allow the use of matrix preconditioning to be reduced or eliminated, can also be checked for and certified –- notably including in the small-field case, where this presently has the greatest impact on the efficiency of the computation.

Recent literature on iOS security has focused on the malicious potential of third-party applications, demonstrating how developers can bypass application vetting and code-level protections. In addition to these protections, iOS uses a generic sandbox profile called "container" to confine malicious or exploited third-party applications. In this paper, we present the first systematic analysis of the iOS container sandbox profile. We propose the SandScout framework to extract, decompile, formally model, and analyze iOS sandbox profiles as logic-based programs. We use our Prolog-based queries to evaluate file-based security properties of the container sandbox profile for iOS 9.0.2 and discover seven classes of exploitable vulnerabilities. These attacks affect non-jailbroken devices running later versions of iOS. We are working with Apple to resolve these attacks, and we expect that SandScout will play a significant role in the development of sandbox profiles for future versions of iOS.

Mobile applications - or apps - are one of the main reasons for the unprecedented success smart phones and tablets have experienced over the last decade. Apps are the main interfaces that users deal with when engaging in online banking, checking travel itineraries, or browsing their social network profiles while on the go. Previous research has studied various aspects of mobile application security including data leakage and privilege escalation through confused deputy attacks. However, the vast majority of mobile application research targets Google's Android platform. Few research papers analyze iOS applications and those that focus on the Apple environment perform their analysis on comparatively small datasets (i.e., thousands in iOS vs. hundreds of thousands in Android). As these smaller datasets call into question how representative the gained results are, we propose, implement, and evaluate CRiOS, a fully-automated system that allows us to amass comprehensive datasets of iOS applications which we subject to large-scale analysis. To advance academic research into the iOS platform and its apps, we plan on releasing CRiOS as an open source project. We also use CRiOS to aggregate a dataset of 43,404 iOS applications. Equipped with this dataset we analyze the collected apps to identify third-party libraries that are common among many applications. We also investigate the network communication endpoints referenced by the applications with respect to the endpoints' correct use of TLS/SSL certificates. In summary, we find that the average iOS application consists of 60.2% library classes and only 39.8% developer-authored content. Furthermore, we find that 9.32% of referenced network connection endpoints either entirely omit to cryptographically protect network communications or present untrustworthy SSL certificates.

Virtualization technology has become ubiquitous in the computing world. With it, a number of security concerns have been amplified as users run adjacently on a single host. In order to prevent attacks from both internal and external sources, the networking of such systems must be secured. Network intrusion detection systems (NIDSs) are an important tool for aiding this effort. These systems work by analyzing flow or packet information to determine malicious intent. However, it is difficult to implement a NIDS on a virtualized system due to their complexity. This is especially true for the Xen hypervisor: Xen has incredible heterogeneity when it comes to implementation, making a generic solution difficult. In this paper, we analyze the network data flow of a typical Xen implementation along with identifying features common to any implementation. We then explore the benefits of placing security checks along the data flow and promote a solution within the hypervisor itself.

Web applications are a frequent target of successful attacks. In most web frameworks, the damage is amplified by the fact that application code is responsible for security enforcement. In this paper, we design and evaluate Radiatus, a shared-nothing web framework where application-specific computation and storage on the server is contained within a sandbox with the privileges of the end-user. By strongly isolating users, user data and service availability can be protected from application vulnerabilities. To make Radiatus practical at the scale of modern web applications, we introduce a distributed capabilities system to allow fine-grained secure resource sharing across the many distributed services that compose an application. We analyze the strengths and weaknesses of a shared-nothing web architecture, which protects applications from a large class of vulnerabilities, but adds an overhead of 60.7% per server and requires an additional 31MB of memory per active user. We demonstrate that the system can scale to 20K operations per second on a 500-node AWS cluster.

Among the current Wi-Fi two security models (Enterprise and Personal), while the Enterprise model (802.1X) offers an effective framework for authenticating and controlling the user traffic to a protected network, the Personal model (802.11) offers the cheapest and the easiest to setup solution. However, the drawback of the personal model implementation is that all access points and client radio NIC on the wireless LAN should use the same encryption key. A major underlying problem of the 802.11 standard is that the pre-shared keys are cumbersome to change. So if those keys are not updated frequently, unauthorized users with some resources and within a short timeframe can crack the key and breach the network security. The purpose of this paper is to propose and implement an effective method for the system administrator to manage the users connected to a router, update the keys and further distribute them for the trusted clients using the Freescale embedded system, Infrared and Bluetooth modules.

Hardware Trojans are an emerging threat that intrudes in the design and manufacturing cycle of the chips and has gained much attention lately due to the severity of the problems it draws to the chip supply chain. Hardware Typically, hardware Trojans are not detected during the usual manufacturing testing due to the fact that they are activated as an effect of a rare event. A class of published HTs are based on the geometrical characteristics of the circuit and claim to be undetectable, in the sense that their activation cannot be detected. In this work we study the effect of continuously monitoring the inputs of the module under test with respect to the detection of HTs possibly inserted in the module, either in the design or the manufacturing stage.